The COVID-19 pandemic has led to a significant increase in the demand for digital technology. Organisations are relying on data for decision-making, making analytics and data science skills highly sought after globally.

Data scientists are in high demand in Singapore, which is considered a top emerging job in the region by LinkedIn. Data analytics plays a crucial role in Singapore’s economy, contributing at least S$1 billion (US$730 million) annually. The value of big data and business analytics services in the region is projected to reach US$27 billion (SG$37 billion) by 2022. 

Effective communication of data analysis will be a key skill as Singapore focuses on its Smart Nation initiatives, and businesses increasingly rely on data for decision-making and growth. The pandemic has accelerated the adoption of data-driven strategies, especially in sectors like retail, healthcare, and food and beverage. Financial services have also utilized data for business strategies and problem-solving for years.

Data is now seen as a competitive advantage, but in the future, it will be essential for all businesses. Data science and analytics expertise will become common skills across organizations, beyond just engineering or IT departments. Businesses will seek top talent in the field to stay competitive.

Also Read: Mind the trust gap: How does a company develop consumer trust through data stewardship?

To succeed, data scientists must go beyond mastering data-related software and programs. They should focus on translating their knowledge into actionable insights and compelling stories that resonate with stakeholders.

Key skills for future data scientists include:

Go back to the basics: Communicating probability, statistics, mathematics, and more

Data scientists should enhance their data literacy skills to bridge the gap between technical and non-technical stakeholders. Communicating fundamental concepts such as variance, standard deviation, and distributions will help in explaining data collection and validity to others.

Simplicity and clarity in data explanations are crucial for engaging with executives and stakeholders from different teams.

Be a data storyteller: Communicating data in an understandable way

Storytelling can improve information retention rates, making data more memorable. Data scientists should craft narratives around data sets to provide context and highlight key insights for the audience.

Data storytelling breaks down communication barriers and makes information digestible and actionable for stakeholders.

Get creative: Visualizing data to make an impact

Visual representations of data enhance communication by contextualizing complex information. Utilizing graphs and charts can help stakeholders quickly understand and extract key insights from data sets.

Finally, stay curious: Balancing learning and teaching

Continuous learning is essential for data scientists to stay relevant. Exploring new data techniques, trends, and software programs can enhance their value within an organization and improve their ability to share insights effectively.

Effective communication and actionable insights will be the language of the future for organizations. Data scientists who excel in explaining processes and presenting findings in engaging ways will be invaluable in driving business success.

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This article was first published on July 19, 2021

The post Why tomorrow’s data scientists need storytelling skills to succeed? appeared first on e27.